Results of the EU NanoSafety Cluster Modelling Projects

Supported by the 7th Framework Programme

data.enanomapper.net

eNanoMapper / Database

Nano Database

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Database Name: data.enanomapper.net
Project: eNanoMapper
Description: Aggregation of data from various sources.
Types of NMs involved: various
Link to Database

JaqPot Quattro

eNanoMapper / Tool

Tools

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Application Name: JaqPot Quattro
Project: eNanoMapper
Description:JaqPot Quattro can be considered as an extendable suite of computational tools under a common framework. Current functionalities include creation of datasets suitable for modelling, training and validation of nanoQSAR models and use of models for calculating predictions.  
Architecture of Tool: REpresentational State Transfer (REST)
Link to download the tool / access the web interface

DCW based on quasi-SMILES

NanoPuzzles, PreNanoTox / Descriptor

Descriptors

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Descriptor name: DCW based on quasi-SMILES
Project: NanoPUZZLES, PreNanoTox
Description: Sum of correlation weights of features related to nanomaterials encoded in the quasi-SMILES strings.
Link to description / publication

Quasi-SMILES and nano-QFAR

PreNanoTox / Model

Models

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Model name: Quasi-SMILES and nano-QFAR: United model for mutagenicity of fullerene and MWCNT under different conditions
Project: PreNanoTox
Description: QSAR model, based on quasi-SMILE, for predicting mutagenicity of fullerene and MWCNT under different conditions.
Types of NMs involved: fullerene and MWCNTs
Link to description / publication

Nano-QSAR

MODERN / Model

Models

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Model name: Nano-QSAR: Genotoxicity of Multi-Walled Carbon Nanotube
Project: MODERN
Description: QSAR model for the prediction the genotoxicity of carbon nanotubes. Experimental data on the bacterial reverse mutation test (TA100) on multiwalled carbon nanotubes was used in combination with quasi-SMILES to develop the models.
Types of NMs involved: MWCNTs
Link to description / publication

search.data.enanomapper.net

eNanoMapper / Database

Databases

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Database Name: search.data.enanomapper.net
Project: eNanoMapper
Description: Search integration, integrates data.enanomapper.net and caNanoLab.
Types of NMs involved: various
Link to Database

Triplestore and SPARQL Endpoint

eNanoMapper / Database

Databases

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Database Name: eNM Triplestore and SPARQL Endpoint
Project: eNanoMapper
Description: Aggregation of data and ontologies.
Types of NMs involved: /
Link to Database

Effective coarse-grained potentials

MembraneNanoPart / Database

Databases

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Database Name: Effective coarse-grained potentials for DMPC, DOPC and DSPC lipids
Project: MembraneNanoPart
Database Description: Coarse-grained potential used to build lipid bilayers models.
Types of NMs involved: /
Link to Database

SiO2-database

MOD-ENP-TOX / Database

Databases

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Database Name: SiO2-database
Project: MOD-ENP-TOX
Database Description: Structured collection of literature data.
Types of NMs involved: SiO2
Link to Database / NA - contact Peter Hoet

nano-lazar

eNanoMapper / Database, Tool, Model

Tools, Databases, Models

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Database / Application / Model Name: nano-lazar
Project: eNanoMapper
Database Description: Mirror of eNM data.
Tool / Model Description: Read across predictions for nanoparticles.
Types of NMs involved: Gold particles from the Protein Corona dataset
Architecture of Tool: Web application, Library
Link to download the tool / access the web interface

RRegrs

eNanoMapper / Tool

Tools

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Application Name: RRegrs
Project: eNanoMapper
Description:RRegrs is an R package for computer-aided model selection for multiple regression methodologies by means of an extensive cross-validation scheme.  
Architecture of Tool: R package
Link to download the tool / access the web interface

Image descriptors

eNanoMapper / Tool

Tools

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Application Name: Image descriptors calculation tool
Project: eNanoMapper
Description: Tool for automated calculation of descriptors from images of nanomaterials. 
Architecture of Tool: Web application
Link to download the tool / access the web interface

Go Descriptor Tool

eNanoMapper / Tool

Tools

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Application Name: Gene Ontology descriptor calculation tool
Project: eNanoMapper
Description: Tool that calculates a class of descriptors derived by clustering methodology of omics and Gene Ontology pathway data developed within the eNanoMapper project.
Architecture of Tool: R package
Link to download the tool / access the web interface (not released yet)

OpenBabel, CDK and JoeLib

eNanoMapper / Descriptor, Tool

Descriptors, Tools

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Descriptor / Application Name: OpenBabel, CDK and JoeLib descriptors
Project: eNanoMapper
Description: Descriptors for core and coating structures.
Architecture of Tool: Web application, Library
Link to download the tool/access the web interface
Link to description / publication

ambit.js

eNanoMapper / Tool

Tools

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Application Name: ambit.js
Project: eNanoMapper
Description: JavaScript client library for the eNanoMapper / AMBIT API. 
Architecture of Tool: Library
Link to download the tool / access the web interface

RENM

eNanoMapper / Tool

Tools

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Application Name: RENM
Project: eNanoMapper
Description: R client library for the eNanoMapper API.
Architecture of Tool: Library
Link to download the tool / access the web interface

Ontology Viewer

eNanoMapper / Tool

Tools

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Application Name: eNM Ontology Viewer
Project: eNanoMapper
Description: Graphical interface for the eNM Triplestore. 
Architecture of Tool: Web application
Link to download the tool / access the web interface

QSAR model for the cell viability

NanoPuzzles, PreNanoTox / Model

Models

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Model name: QSAR model for the cell viability(%) of cultured human embryonic kidney cells exposed to nanoparticles
Project: NanoPUZZLES, PreNanoTox
Description: QSAR model for predicting cell viability(%) of cultured human embryonic kidney based on quasi-SMILES encoding physico-chemical properties of nanoparticles and experimental conditions.
Types of NMs involved: SiO2
Link to description / publication

Optimal descriptor as a translator

NanoPuzzles / Model

Models

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Model name: Optimal descriptor as a translator of eclectic data into prediction of cytotoxicity for metal oxide nanoparticles under different conditions
Project: NanoPUZZLES
Description: QSAR model for predicting photo-induced toxicity to bacteria Escherichia coli based on quasi-SMILES to represent data on various nanoparticles under different physicochemical conditions.
Types of NMs involved: various metal oxide nanoparticles
Link to description / publication

Optimal descriptor as a translator

NanoPuzzles / Model

Models

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Model name: Optimal descriptor as a translator of eclectic information into the prediction of membrane damage
Project: NanoPUZZLES
Description: QSAR model for predicting membrane damage based on quasi-SMILES to represent data on various nanoparticles under different physicochemical conditions.
Types of NMs involved: ZnO and TiO2
Link to description / publication

A quasi-QSPR modeling

PreNanoTox / Model

Models

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Model name: A quasi-QSPR modeling for the photocatalytic decolorisation rate constants and cellular viability (CV%) of nanoparticles by CORAL
Project: PreNanoTox
Description: QSAR model for predicting the photocatalytic decolorisation rate constants and cellular viability (CV%) of nanoparticles,based on quasi-SMILE encoding physico-chemical properties of nanoparticles and different experimental conditions.
Types of NMs involved: nanoparticles
Link to description / publication

Monte Carlo method

PreNanoTox / Model

Models

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Model name: Application of the Monte Carlo method to prediction of dispersibility of graphene in various solvents
Project: PreNanoTox
Description: QSPR model, based on SMILE, for predicting the dispersibility of graphene in various solvents.
Types of NMs involved: graphene
Link to description / publication

Size-dependent Nanodescriptors

MODERN / Descriptor, Tool

Descriptors, Tools

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Descriptor name: Size-dependent Nanodescriptors for Metal Oxide Nanoparticles
Application name: Size-dependent Nanodescriptors
Project: MODERN
Description of Descriptor: Nanodescriptors are calculated using force field based methods in LAMMPS (Large-scale Atomic /Molecular Massively Parallel Simulator). Nanoparticle structures were derived from the thermodynamically most stable crystal structures of the respective bulk metal oxides. Unit cells of the metal oxides were replicated in all three dimensions to generate spherical nanoparticles with the random addition of oxygen or metal atoms to ensure electroneutrality. Buckingham potential and Wolf summation are used to calculate potential energies and coulombic interactions, respectively.
Description of Tool: Web-based application for the calculation of nanodescriptors for Metal Oxide Nanoparticles.
Architecture of Tool: Web application
Link to description / publication
Link to download the tool / access the web interface

Coarse-grained model

MembraneNanoPart / Tool

Tools

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Application Name: Coarse-grained model of adsorption of blood plasma proteins onto nanoparticles
Project: MembraneNanoPart
Description: Scripts and data needed to calculate the interaction of HSA for a given orientation with a 50 nm negative charged hydrophobic NP. See Lopez and Lobaskin for more details [J. Chem. Phys. 143, 243138 (2015)].
Architecture of Tool: Espresso Input files
Link to download the tool / access the web interface

Coarse-grained DMPC

MembraneNanoPart / Tool

Tools

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Application Name: Coarse-grained DMPC and Nanoparticle model
Project: MembraneNanoPart
Description: This file contains all the input files needed to run the simulation of a 10, 15, 20 or 25 nm particle adsorbing onto bilayers a DMPC bilayer.
Architecture of Tool: Gromacs Input files
Link to download the tool / access the web interface

CG lipid fragments with amino acids

MembraneNanoPart / Database

Databases

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Database Name: Potentials of mean force for CG lipid fragments with amino acids
Project: MembraneNanoPart
Database Description: Interaction potentials between coarse-grained lipid fragments and aminos acids. Can be used to study the adsorption of proteins on lipid bilayers.
Types of NMs involved: /
Link to Database

GO descriptors

eNanoMapper / Descriptor

Descriptors

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Descriptor name: Gene Ontology descriptors
Project: eNanoMapper
Description: A class of descriptors derived by clustering methodology of omics and Gene Ontology pathway data developed within the eNanoMapper project. 
Link to description / publication

Model for six blood proteins

MembraneNanoPart / Database

Databases

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Database Name: Coarse-grained model for six blood proteins
Project: MembraneNanoPart
Database Description: Coordinate files for Coarse-Grained models of six common blood proteins.
Types of NMs involved: /
Link to Database

MagiC

MembraneNanoPart / Tool

Tools

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Application Name: MagiC
Project: MembraneNanoPart
Description: Software to build molecular coarse-grained models from atomistic simulations.
Architecture of Tool: Software application
Link to download the tool / access the web interface

Images-based descriptors

NanoPuzzles / Descriptor

Descriptors

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Descriptor name: Microscopic images-based descriptors
Project: NanoPUZZLES
Description: Descriptors derived from computational processing of microscopic (SEM/TEM/AFM) images of the nanoparticles.
Link to description / publication

SiO2 quartz with amino acids

MembraneNanoPart / Database

Databases

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Database Name: Potentials of mean force for SiO2 quartz with amino acids
Project: MembraneNanoPart
Database Description: Interaction potentials that can be used to study the adsorption of amino acids onto SiO2 quartz.
Types of NMs involved: SiO2 quartz
Link to Database

SiO2 amorphous with amino acids

MembraneNanoPart / Database

Databases

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Database Name: Potentials of mean force for SiO2 amorphous with amino acids
Project: MembraneNanoPart
Database Description: Interaction potentials that can be used to study the adsorption of amino acids onto SiO2 amorphous.
Types of NMs involved: SiO2 amorphous
Link to Database

CdSe with amino acids

MembraneNanoPart / Database

Databases

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Database Name: Potentials of mean force for CdSe with amino acids
Project: MembraneNanoPart
Database Description: Interaction potentials that can be used to study the adsorption of amino acids onto SiO2 quartz.
Types of NMs involved: CdSe
Link to Database

TiO2 and Gold with amino acids

MembraneNanoPart / Database

Databases

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Database Name: Potentials of mean force for TiO2 and Gold with amino acids
Project: MembraneNanoPart
Database Description: Interaction potentials that can be used to study the adsorption of amino acids onto TiO2 and Gold.
Types of NMs involved: TiO2, Gold
Link to Database

Estimation of energy barrier

MembraneNanoPart / Database

Databases

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Database Name: MS Excel spreadsheet for estimation of energy barrier for penetration of NPs through lipid bilayers
Project: MembraneNanoPart
Database Description: Tool to estimate the adsorption energy of TiO2 adsorbing onto DMPC.
Types of NMs involved: TiO2
Link to Database

Slipids model for lipid bilayer

MembraneNanoPart / Tool

Tools

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Application Name: Slipids model for lipid bilayer interacting with Gold nanoparticles
Project: MembraneNanoPart
Description: This file contains all the input files needed to run a simulation of a 3nm, 5nm or 10 nm gold particles adsorbing onto bilayers of various size. Also included are the files for a single lipid PMF as it adsorbs onto a gold surface.
Architecture of Tool: Gromacs Input files
Link to download the tool / access the web interface

DMPC lipid bilayer

MembraneNanoPart / Database

Databases

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Database Name: Potentials of mean force for penetration of a C60 particle through a DMPC lipid bilayer
Project: MembraneNanoPart
Database Description: Interaction potentials that can be used to study the penetration of C60 into DMPC bilayers.
Types of NMs involved: C60
Link to Database

Quantitative Structure-Activity

MODERN / Model

Models

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Model name: Quantitative Structure-Activity Relationships for Cellular Uptake of Surface-Modified Nanoparticles
Project: MODERN
Description: Quantitative structure-activity relationships (QSARs) were developed, for cellular uptake of nanoparticles (NPs) of the same iron oxide core but with different surface-modifying organic molecules, based on linear and non-linear (epsilon support vector regression (ε-SVR)).
Types of NMs involved: Iron oxide nanoparticles with different surface modifications
Link to description / publication

Development of structure–activity

MODERN / Model

Models

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Model name: Development of structure–activity relationship for metal oxide nanoparticles
Project: MODERN
Description: Nanomaterial structure–activity relationships (nano-SARs) for metal oxide nanoparticles (NPs) toxicity were investigated using metrics based on dose–response analysis and consensus self-organizing map clustering. various nano-SAR building models were developed and evaluated, based on an initial pool of thirty NP descriptors.
Types of NMs involved: various metal oxide nanoparticles
Link to description / publication

Association rules

MODERN / Model

Models

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Model name: Association rules for cellular responses induced by metal and metal oxide nanoparticles
Project: MODERN
Description: Relationships among fourteen different biological responses (including ten signaling pathway activities and four cytotoxicity effects) of murine macrophage (RAW264.7) and bronchial epithelial (BEAS-2B) cells exposed to six metal and metal oxide nanoparticles (NPs) were analyzed using both statistical and data mining approaches.
Types of NMs involved: various metal and metal oxide nanoparticles
Link to description / publication

Predicting Cell Association

MODERN / Model

Models

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Model name: Predicting Cell Association of Surface-Modified Nanoparticles Using Protein Corona Structure - Activity Relationships (PCSAR)
Project: MODERN
Description: A weighting technique was applied to construct specific signatures that represent the corona composition for each nanoparticle. Using this basic set of protein descriptors, a new Protein Corona Structure-Activity Relationship (PCSAR) that relates net cell association with the physicochemical descriptors of the proteins that form the corona was developed and validated.
Types of NMs involved: Surface-Modified gold and silver nanoparticles
Link to description / publication

Chemistry Develop Kit descriptors

eNanoMapper / Descriptor

Descriptors

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Descriptor name: Chemistry Develop Kit descriptors (structural descriptors)
Project: eNanoMapper
Description: Nanomaterial descriptors implemented as part of the Chemistry Development Kit.
Link to description / publication

NanoWiki

eNanoMapper / Database

Databases

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Database Name: NanoWiki
Project: eNanoMapper
Description: /
Types of NMs involved: mostly metal oxides
Link to Database

CORAL

NanoPUZZLES, PreNanoTox / Tool

Tools

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Application Name: CORAL
Project: NanoPUZZLES, PreNanoTox
Description: Software to build up models for nanomaterials.
Architecture of Tool: Standalone application
Link to download the tool / access the web interface

ISA-TAB-Nano datasets

NanoPuzzles / Database

Databases

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Database Name: NanoPUZZLES ISA-TAB-Nano datasets
Project: NanoPUZZLES
Description: Toxicity and cytotoxicity data extracted from literature references.
Types of NMs involved: various
Link to Database

Liquid drop model (LDM)

NanoPuzzles / Descriptor

Descriptors

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Descriptor name: Liquid drop model (LDM)
Project: NanoPUZZLES
Description: In LDM, a nanoparticle is represented as a spherical drop, where elementary particles (molecules) are densely packed and the density of cluster is equal to mass density.
Link to description / publication

Causal inference methods

NanoPuzzles / Model

Models

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Model name: Causal inference methods
Project: NanoPUZZLES
Description: Causal inference methods to assist in mechanistic interpretation of classification nano-SAR models.
Types of NMs involved: various metal oxide nanoparticles
Link to description / publication

Nanosafety data management system

MODERN / Tool

Tools

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Application Name: ISA-TAB-Nano compliant nanosafety data management system
Project: MODERN
Description: nanoDMS is a data management system that implements the Nano extension of the ISA-TAB data sharing format (ISA-TAB-Nano) which specifies a format for representing and sharing information about nanomaterials, small molecules and biological specimens along with their assay characterization data using spreadsheet or TAB-delimited files.
Architecture of Tool: Web application
Link to download the tool / access the web interface

Multidendrograms

MODERN / Tool

Tools

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Application Name: Multidendrograms
Project: MODERN
Description: MultiDendrograms is a simple yet powerful program to make the Hierarchical Clustering of real data, distributed under an Open Source license. Starting from a distances (or similarities) matrix, MultiDendrograms calculates its dendrogram using the most common Agglomerative Hierarchical Clustering algorithms, allows the tuning of many of the graphical representation parameters, and the results may be easily exported to file.
Architecture of Tool: Standalone application
Link to download the tool / access the web interface

Pathway Analysis (ANAPATH)

MODERN / Tool

Tools

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Application Name: Pathway Analysis (ANAPATH)
Project: MODERN
Description: Tool for the integrated analysis of genes and pathways based on gene co-annotation. Preprocessed E-Coli and C.Elegans networks are available.
Architecture of Tool: Web application
Link to download the tool / access the web interface

PreNanoTox - NP Toxicity Browser

PreNanoTox / Tool

Tools

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Application Name: PreNanoTox - NP Toxicity Browser
Project: PreNanoTox
Description: Web based browser for NP toxicity experimental data retrieved from literature.
Architecture of Tool: Web application
Link to download the tool / access the web interface

eNanoMapper

EU funded Project

eNanoMapper
Computational infrastructure for toxicological data management of engineered nanomaterials

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About the Project:
eNanoMapper (ENM) proposes a computational infrastructure for toxicological data management of engineered nanomaterials (ENMs) based on open standards, ontologies and an interoperable design to enable a more effective, integrated approach to European research in nanotechnology. eNanoMapper is supporting the collaborative safety assessment for ENMs by creating a modular, extensible infrastructure for transparent data sharing, data analysis, and the creation of computational toxicology models for ENMs. Building on recent developments of consortium partners in predictive toxicology, biology and nanotechnology research, eNanoMapper is developing resources, tools and standards for a scientifically sound risk assessment of ENMs that will support the design of new safe and environment-friendly ENMs as well as the assessment of existing materials. 

Link to the website

NanoPUZZLES

EU funded Project

NanoPUZZLES
Modelling toxicity behaviour of engineered nanoparticles

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About the Project:
The main objective of the NanoPUZZLES project is to develop a package of computational algorithms for the comprehensive modelling of the relationships between the structure, properties, molecular interactions and toxicity of selected classes of engineered nanoparticles (NPs). The package will serve as a proof-of-the-concept that the risk related to NPs can be comprehensively assessed with use of computational techniques and will define a basis for development of further modelling techniques for a large variety of nanoparticles.

The project is focusing on two groups of compounds: inorganic engineered nanoparticles (metal nanooxides) and carbon nanoparticles (carbon nanotubes (single-walled and multi-walled), fullerenes and fullerene derivatives). That choice was dictated by the wide application of these nanoparticles in everyday household products, and by the fact that these compounds are commercially available in the market which eliminates the necessity for their synthesis (reduction of costs). 

Link to the website

PreNanoTox

EU funded Project

PreNanoTox
Predictive Toxicology of Engineered Nanoparticles

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About the Project:
The production of many consumer products based on manufactured nanoparticles (NPs) has led to growing public and regulatory concern about the safety of nanomaterials. Since experimental toxicological testing of NPs is costly and time-consuming, it is necessary to develop a new research field based on knowledge, methods and tools to reach the goal of predictive nanotoxicology. The PreNanoTox consortium addresses three currently missing critical elements needed to develop a platform for predictive nanotoxicology: (1) There is a current lack of a unified large database, leading to our suggestion to form such database by applying cutting edge information extraction tools on a large repository of scientific articles; (2) There is a need for better understanding of the underlying mechanisms of the primary interaction of NP with the cell membrane. It is suggested to apply appropriate theory and simulation assuming that the surface chemistry of a NP (affecting e.g. NP’s surface reactivity, hydrophobicity, or surface electrostatics) as well as other physical properties (e.g. size and shape) determine the extent of adsorption of NPs to a cell surface, leading eventually to an uptake of the NPs; (3) There is a need to extend the traditional Quantitative Structure-Activity Relationship QSAR paradigm to the field of nanotoxicology. This will be carried out by linking appropriate NP descriptors, with emphasis on those which determine the extent of adsorption of NPs to cells, with biological responses. The PreNanoTox consortium is made up of four research groups (from three scientific organizations), which lead in information technology, soft matter modelling, computational chemistry and in-vitro toxicology, yielding a synergetic output.  

Link to the website

MODERN

EU funded Project

MODERN
Modeling Nanotoxicity

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About the Project:
MODERN is an international interdisciplinary research team capable of undertaking the challenging task of modeling the environmental and human health effects resulting from exposure to eNPs.

The primary objective of MODERN is to develop a new robust framework suitable for evaluating the environmental and health impact of eNPs. This encompasses:

-the identification of eNP categories,
-he development of new [Quantitative] Nanostructure-Property Relationship ([Q]NPR) and [Quantitative] Nanostructure-Activity Relationship ([Q]NAR) models to relate intrinsic molecular (nanostructure) and physicochemical properties of nanoparticles with their adverse effects (e.g., toxicity), and
-the establishment of hazard ranking and safe-by-design strategies. This objective is a challenging task since fundamental information (experimental or theoretical) regarding mechanisms of nano-bio interactions is limited.

Therefore, new fundamental knowledge and novel computational tools suitable to characterize eNPs in terms of their physicochemical and structural properties as well as their bioavailability and toxicity/safety in biological systems are required.  

Link to the website

MembraneNanoPart

EU funded Project

MembraneNanoPart
Modelling the mechanisms of nanoparticle-lipid interactions and nanoparticle effects on cell membrane structure and function

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About the Project:
The goal of MembraneNanoPart is to develop physically justified models and computational tools to quantitatively describe and understand the molecular mechanisms of nanoparticle-cell membrane interactions, which we consider to be a crucial point in any predictive model of nanoparticle toxicity. We will address the mechanisms of nanoparticle protein corona formation, the protective function of the membrane, nanoparticle uptake into the cell, and the effect of nanoparticles on the cell membrane. We plan to develop a consistent multiscale simulation scheme starting from nanoparticle-biomolecule interaction at the atomistic scale using molecular dynamics simulation, and then systematically constructing coarse-grained mesoscale models for simulating the structure and dynamics of the cell membrane perturbed by nanoparticles at the physiologically relevant time and length scales. We will develop and test a universal method for evaluating the rates of nanoparticle translocation through membranes. Based on the information acquired from the simulations and analyzed together with available experimental data, the toxicological impact will be deduced. We will apply our approach to a range of common engineered nanoparticles, relating their physicochemical properties such as size and shape, surface charge, hydrophobicity and hydrophilicity, to the toxicological effects and develop a test suite allowing to make toxicity prediction on the basis of purely computational or limited in vitro screening tests.  

Link to the website

MOD-ENP-TOX

EU funded Project

MOD-ENP-TOX
Modeling Platform to Predict the Toxicity of Metal-based Nanoparticles

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About the Project:
MOD-ENP-TOX project is a multidisciplinary project aiming to accomplish the following objectives: (i) to develop a novel and rational “Modelling Assay Platform (MAP)” which can be used as a « Risk Indicator » tool to predict the toxicity of metal-based NPs (MeNPs), and (ii) to demonstrate the feasibility of a MAP prototype – on a shortlist of MeNPs - which can be further developed to screen the toxicity of a large number ENPs. Based on the concept of Integrating Testing Strategies (ITS), the proposed generic MAP combines two main and complimentary paradigms: (1) a novel Computational Modeling Package (CMP) based on structural, mechanistic, as well as kinetic modeling tools and (2) an innovative screening (IS) strategy that allows performing multiplexed streamlined assays for calibration, refinement and validation of the computed models.  

First a series of classification algorithms will be applied to identify MeNPs with similar toxicity patterns, then computational modelling tools will be developed to establish a more rational relationship between MeNPs descriptors and their toxicity in a dynamic and quantitative way. An in-vitro/in-vivo IS paradigm will be developed as a scalable assessment tool to calibrate and validate the predictive power of the CMP using subsets of the training set or independent set of MeNPs (validation set) respectively.  

Link to the website

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